Machine Learning / Data Engineer - Reco & Lifestyle Intelligence (All Genders)

Zalando SE; Zürich; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Benefits dieser Stelle

Employee shares program

Discounts on fashion & beauty

2 paid volunteering days

25 days vacation

Health and wellbeing options

Swiss SBB Halbtax

Mental health support

Training platform & peer reviews

Zusammenfassung

Zalando SE in Zürich, Switzerland is seeking a Machine Learning / Data Engineer in Recommendations & Lifestyle Intelligence. You will design, deploy, and scale end-to-end ML and GenAI systems powering 100+ data pipelines for 60+ million Zalando customers, collaborating with Applied Scientists, Product Managers, and Data Engineers.

You will own the full ML lifecycle—from feature engineering and offline training to online inference, monitoring, and MLOps infrastructure, with emphasis on high

Qualifikationen

• 2+ years of experience with PySpark, ML Ops, AWS, Airflow, Python and deep learning frameworks.
• Proven productionizing ML models and orchestrating ML workflows.
• Experience with PySpark on Databricks (or similar) for scalable data processing and ML inference.
• Excellent written and spoken English; ability to communicate complex topics clearly.
• Experience with feature stores or real-time feature engineering is a plus.

Aufgaben

• Build and optimize ML pipelines for training, deploying, and monitoring AI models.
• Productionize ML models by orchestrating workflows and deploying scalable solutions on AWS.
• Improve data quality and reliability for real-time and batch inference systems.

Kenntnisse

PySpark

ML Ops

AWS

Apache Airflow

Python

Deep learning (PyTorch)

Databricks

Kubernetes

SageMaker

CloudFormation

Tools

PySpark

Apache Airflow

Databricks

Kubernetes

SageMaker

CloudFormation

Python

PyTorch

Jobbeschreibung

THE ROLE & THE TEAM

The Reco & Lifestyle Intelligence team is at the forefront of realizing Zalando’s AI ambition, We build the customer and assortment understanding that lets Zalando reason about why a product fits a given customer, and translate that understanding into discovery experiences that go beyond similarity-based recommendation. The team builds core, foundational capabilities like customer and assortment intelligence powered by advanced embeddings, sequential modeling, and outfit intelligence. In parallel, the team builds interactive UX components delivering tailored product suggestions across our customer journeys, where the foundational capabilities could be integrated with. As a Machine Learning / Data Engineer in Recommendations & Lifestyle Intelligence, you will design, deploy, and scale end-to-end ML and GenAI systems powered by 100+ data pipelines for 60+ million Zalando customers. Collaborating closely with Applied Scientists, Product Managers, and Data Engineers, you will translate cutting-edge models into high-throughput, low-latency production microservices. You will take ownership of the full ML lifecycle - from feature engineering and offline training to online inference, continuous monitoring, and MLOps infrastructure.

INCLUSIVE BY DESIGN

At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce - one that is inclusive by design. We only assess candidates based on qualifications, merit, and business needs. We welcome applications from people of all gender identities, sexual orientations, personal expressions, racial identities, ethnicities, religious beliefs, and disability statuses. We only want to know why you’re great for this role, so please avoid including your picture, age, and marital status in your CV as well. We want to provide you with a great candidate experience. Please feel free to inform us of any accommodations you may need, so we can best support and assist you throughout the hiring process.

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)

• Build and optimise ML pipelines for training, deploying, and monitoring AI models.
• Productionize ML models by orchestrating workflows (Apache Airflow) and deploying scalable, reliable solutions on AWS for real-time and batch inference.
• Improve data quality and reliability for real-time and batch inference systems.

• WE’D LOVE TO MEET YOU IF 2+ years of experience with PySpark, ML Ops, AWS (SageMaker, CloudFormation), Apache Airflow, Python and deep learning frameworks (e.g. PyTorch).
• Proven experience in productionizing ML models and orchestrating ML workflows.
• Experience with PySpark on Databricks (or similar) for scalable data processing and ML model inference.
• You possess excellent communication skills in English and can articulate complex technical topics and solutions clearly and concisely.
• Experience with feature stores, real-time feature engineering or Kubernetes is a plus.

OUR OFFER

• Employee shares program
• 40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners
• 2 paid volunteering days a year
• 25 days of vacation a year for full-time employees
• Health and wellbeing options (SportAbo in Zurich)
• Swiss SBB Halbtax (half-fare card)
• Mental health support and coaching available
• Drive your development through our training platform and biannual peer-to-peer review

It’s the perfect time to join Zalando on our journey, from being a pioneer in the world of e-commerce, to the Starting Point for Fashion in Europe. We connect customers, brands, and partners across 25 markets. Help us drive digital and sustainable solutions for fashion, logistics, advertising and research, bringing head-to-toe fashion to 50 million active customers through a team of diverse skill-sets, cultural backgrounds, and interests. Our values do.More - our sustainability strategy Follow us on Instagram: instagram.com/insidezalando